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The Entropy of Co-Compact Open Covers

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The Entropy of Co-Compact Open Covers Entropy 2013, 15, 2464-2479; doi:10.3390/e15072464 OPEN ACCESS entropy ISSN 1099-4300 www.mdpi.com/journal/entropy Article The Entropy of Co-Compact Open Covers Zheng Wei 1, Yangeng Wang 2, Guo Wei 3;*, Tonghui Wang 1 and Steven Bourquin 3 1 Department of Mathematical Sciences, New Mexico State University, Las Cruces, NM 88001, USA; E-Mails: [email protected] (Z.W.); [email protected] (T.W.) 2 Department of Mathematics, Northwest University, Xi’an, Shaanxi 710069, China; E-Mail: [email protected] (Y.W.) 3 Department of Mathematics & Computer Science, University of North Carolina at Pembroke, Pembroke, NC 28372, USA; E-Mail:[email protected] (S.B.) * Author to whom correspondence should be addressed; E-Mail:[email protected]; Tel.: +1-910-521-6582; Fax: +1-910-522-5755. Received: 3 April 2013; in revised form: 8 June 2013 / Accepted: 18 June 2013 / Published: 24 June 2013 Abstract: Co-compact entropy is introduced as an invariant of topological conjugation for perfect mappings defined on any Hausdorff space (compactness and metrizability are not necessarily required). This is achieved through the consideration of co-compact covers of the space. The advantages of co-compact entropy include: (1) it does not require the space to be compact and, thus, generalizes Adler, Konheim and McAndrew’s topological entropy of continuous mappings on compact dynamical systems; and (2) it is an invariant of topological conjugation, compared to Bowen’s entropy, which is metric-dependent. Other properties of co-compact entropy are investigated, e.g., the co-compact entropy of a subsystem does not exceed that of the whole system. For the linear system, (R; f), defined by f(x) = 2x, the co-compact entropy is zero, while Bowen’s entropy for this system is at least log 2. More generally, it is found that co-compact entropy is a lower bound of Bowen’s entropies, and the proof of this result also generates the Lebesgue Covering Theorem to co-compact open covers of non-compact metric spaces. Keywords: topological dynamical system; perfect mapping; co-compact open cover; topological entropy; topological conjugation; Lebesgue number Classification: MSC 54H20; 37B40 Entropy 2013, 15 2465 1. Introduction 1.1. Measure-Theoretic Entropy The concept of entropy per unit time was introduced by Shannon [1], by analogy with the standard Boltzmann entropy measuring a spatial disorder in a thermodynamic system. In the 1950s, Kolmogorov [2] and Sinai established a rigorous definition of K-S entropy per unit time for dynamical systems and other random processes [3]. Kolmogorov imported Shannon’s probabilistic notion of entropy into the theory of dynamical systems, and the idea was vindicated later by Ornstein, who showed that metric entropy suffices to completely classify two-sided Bernoulli processes [4], a basic problem, which for many decades, appeared completely intractable. Kolmogorov’s metric entropy is an invariant of measure theoretical dynamical systems and is closely related to Shannon’s source entropy. The K-S entropy is a powerful concept, because it controls the top of the hierarchy of ergodic properties: K-S property ) multiple mixing ) mixing ) weak mixing ) ergodicity [3]. The K-S property holds if there exists a subalgebra of measurable sets in phase space, which generates the whole algebra by application of the flow [3]. The dynamical randomness of a deterministic system finds its origin in the dynamical instability and the sensitivity to initial conditions. In fact, the K-S entropy is related to the Lyapunov exponents, according to a generalization of Pesin’s theorem [5,6]. A deterministic system with a finite number of degrees of freedom is chaotic if its K-S entropy per unit time is positive. More properties about K-S entropy can be found in papers [3,5,7]. The concept of space-time entropy or entropy per unit time and unit volume was later introduced by Sinai and Chernov [8]. A spatially extended system with a probability measure being invariant under space and time translations can be said to be chaotic if its space-time entropy is positive. 1.2. Topological Entropy and Its Relation to Measure-Theoretic Entropy In 1965, Adler, Konheim and McAndrew introduced the concept of topological entropy for continuous mappings defined on compact spaces [9], which is an analogous invariant under conjugacy of topological dynamical systems and can be obtained by maximizing the metric entropy over a suitable class of measures defined on a dynamical system, implying that topological entropy and measure-theoretic entropy are closely related. Goodwyn in 1969 and 1971, motivated by a conjecture of Adler, Konheim and McAndrew [9], compared topological entropy and measure-theoretic entropy and concluded that topological entropy bounds measure-theoretic entropy [10,11]. In 1971, Bowen generalized the concept of topological entropy to continuous mappings defined on metric spaces and proved that the new definition coincides with that of Adler, Konheim and McAndrew’s within the class of compact spaces [12]. However, the entropy according to Bowen’s definition is metric-dependent [13] and can be positive even for a linear function (Example 5.1 or Walters’ book, pp.176). In 1973, along with a study of measure-theoretic entropy, Bowen [12] gave another definition of topological entropy resembling Hausdorff dimension, which also equals to the topological entropy defined by Adler, Konheim and McAndrew when the space is compact. Recently, Canovas´ and Rodr´ıguez, and Malziri and Molaci proposed other definitions of topological entropy for continuous mappings defined on non-compact metric spaces [14,15]. Entropy 2013, 15 2466 1.3. The Importance of Entropy The concepts of entropy are useful for studying topological and measure-theoretic structures of dynamical systems. For instance, two conjugated systems have the same entropy, and thus, entropy is a numerical invariant of the class of conjugated dynamical systems. Upper bounds on the topological entropy of expansive dynamical systems are given in terms of the −entropy, which was introduced by Kolmogorov-Tikhomirov [2]. The theory of expansive dynamical systems has been closely related to the theory of topological entropy [16–18]. Entropy and chaos are closely related, e.g., a continuous mapping, f : I ! I, is chaotic if and only if it has a positive topological entropy [19]. But this result may fail when the entropy is zero, because of the existence of minimum chaotic (transitive) systems [20,21]. A remarkable result is that a deterministic system together with an invariant probability measure defines a random process. As a consequence, a deterministic system can generate dynamical randomness, which is characterized by an entropy per unit time that measures the disorder of the trajectories along the time axis. Entropy has many applications, e.g., transport properties in escape-rate theory [22–26], where an escape of trajectories is introduced by absorbing conditions at the boundaries of a system. These absorbing boundary conditions select a set of phase-space trajectories, forming a chaotic and fractal repeller, which is related to an equation for K-S entropy. The escape-rate formalism has applications in diffusion [27], reaction-diffusion [28] and, recently, viscosity [29]. Another application is the classification of quantum dynamical systems, which is given by Ohya [30]. Symbolic dynamical systems (P(p); σ) have various representative and complicated dynamical properties and characteristics, with an entropy log p. When determining whether or not a given topological dynamical system has certain dynamical complexity, it is often compared with a symbolic dynamical system [21,31]. For the topological conjugation with symbolic dynamical systems, we refer to Ornstein [4], Sinai [32], Akashi [33] and Wang and Wei [34,35]. 1.4. The Purpose, the Approach and the Outlines The main purpose of this article is to introduce a topological entropy for perfect mappings defined on arbitrary Hausdorff spaces (compactness and metrizability are not necessarily required) and investigate fundamental properties of such an entropy. Instead of using all open covers of the space to define entropy, we consider the open covers consisting of the co-compact open sets (open sets whose complements are compact). Various definitions of entropy and historical notes are mentioned previously in this section. Section2 investigates the topological properties of co-compact open covers of a space. Section3 introduces the new topological entropy defined through co-compact covers of the space, which is called co-compact entropy in the paper, and further explores the properties of the co-compact entropy and compares it with Adler, Konheim and McAndrew’s topological entropy for compact spaces. Sections4 investigates the relation between the co-compact entropy and Bowen’s entropy. More precisely, Section4 compares the co-compact entropy with that given by Bowen for systems defined on metric spaces. Because the spaces under consideration include non-compact metric spaces, the traditional Lebesgue Covering Theorem does not apply. Thus, we generalize this theorem to co-compact open covers of non-compact metric spaces. Based on the generalized Lebesgue Covering Theorem, we show that the co-compact entropy Entropy 2013, 15 2467 is a lower bound for Bowen’s entropies. In Section 4.2, a linear dynamical system is studied. For this simple system, its co-compact entropy is zero, which is appropriate, but Bowen’s entropy is positive. 2. Basic Concepts and Definitions Let (X; f) be a topological dynamical system, where X is a Hausdorff and f : X ! X is a continuous mapping. We introduce the concept of co-compact open covers as follows. Definition 2.1 Let X be a Hausdorff space. For an open subset, U of X, if XnU is a compact subset of X, then U is called a co-compact open subset. If every element of an open cover U of X is co-compact, then U is called a co-compact open cover of X.
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